Decorrelating (DECOR) transformations for low-power adaptive filters

Abstract

Presented in this paper are decorrelating transformations (referred to as DECOR transformations) to reduce the power dissipation in adaptive filters. The coefficients generated by the weight update block in an adaptive filter are passed through a decorrelating block such that fewer bits are required to represent the coefficients. Thus, the size of the arithmetic units in the filter (F-block) is reduced thereby reducing the power dissipation. The DECOR transform is well suited for narrow-band filters because there is significant correlation between adjacent coefficients. In addition, the effectiveness of DECOR transforms increases with increase in the order of the filter and decrease in coefficient precision. Simulation results indicate reduction in power dissipation in the F-block ranging from 12% to 38% for filter bandwidths ranging from 0.15 fs to 0.025 fs (where fs is the sample rate).

abstract = "Presented in this paper are decorrelating transformations (referred to as DECOR transformations) to reduce the power dissipation in adaptive filters. The coefficients generated by the weight update block in an adaptive filter are passed through a decorrelating block such that fewer bits are required to represent the coefficients. Thus, the size of the arithmetic units in the filter (F-block) is reduced thereby reducing the power dissipation. The DECOR transform is well suited for narrow-band filters because there is significant correlation between adjacent coefficients. In addition, the effectiveness of DECOR transforms increases with increase in the order of the filter and decrease in coefficient precision. Simulation results indicate reduction in power dissipation in the F-block ranging from 12% to 38% for filter bandwidths ranging from 0.15 fs to 0.025 fs (where fs is the sample rate).",

N2 - Presented in this paper are decorrelating transformations (referred to as DECOR transformations) to reduce the power dissipation in adaptive filters. The coefficients generated by the weight update block in an adaptive filter are passed through a decorrelating block such that fewer bits are required to represent the coefficients. Thus, the size of the arithmetic units in the filter (F-block) is reduced thereby reducing the power dissipation. The DECOR transform is well suited for narrow-band filters because there is significant correlation between adjacent coefficients. In addition, the effectiveness of DECOR transforms increases with increase in the order of the filter and decrease in coefficient precision. Simulation results indicate reduction in power dissipation in the F-block ranging from 12% to 38% for filter bandwidths ranging from 0.15 fs to 0.025 fs (where fs is the sample rate).

AB - Presented in this paper are decorrelating transformations (referred to as DECOR transformations) to reduce the power dissipation in adaptive filters. The coefficients generated by the weight update block in an adaptive filter are passed through a decorrelating block such that fewer bits are required to represent the coefficients. Thus, the size of the arithmetic units in the filter (F-block) is reduced thereby reducing the power dissipation. The DECOR transform is well suited for narrow-band filters because there is significant correlation between adjacent coefficients. In addition, the effectiveness of DECOR transforms increases with increase in the order of the filter and decrease in coefficient precision. Simulation results indicate reduction in power dissipation in the F-block ranging from 12% to 38% for filter bandwidths ranging from 0.15 fs to 0.025 fs (where fs is the sample rate).